SensiML Corp. has partnered with Microchip Technology Inc. to simplify the development of artificial intelligence (AI) code for smart industrial, consumer, and commercial edge Internet-of-Things (IoT) applications. This partnership enables embedded developers using Microchip Technology’s microcontrollers and the powerful MPLAB X IDE tool suite to quickly and easily add intelligence to their new or legacy designs with SensiML’s Analytics Toolkit.
The new integrated design flow enables users to use the Data Visualiser debug tool included with the MPLAB X IDE tool suite to directly read register-level sensor data and then feed that information in SensiML’s Data Capture Lab where it can be analysed and labelled for high-quality AI modelling. This approach means that data from any of the wide range of sensors supported by MPLAB X IDE tool suite can be converted into usable AI models. The models generated by the SensiML tools are extremely efficient and can easily be supported by nearly any Microchip microcontroller and its associated memory subsystem while keeping power consumption extremely low.
SensiML takes the data science complexity out of AI sensing code for smart industrial, consumer, and commercial applications. Typical examples include industrial control, smart buildings, smart cities, and mass transit management.
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“Microchip’s microcontrollers are used all over the world in a broad range of sensor-based applications,” said Chris Rogers, CEO at SensiML. “Our partnership has resulted in an automated design flow in which the SensiML tools can easily tap into sensor data from the MPLAB X IDE and generate machine learning models that transform physical sensor endpoints into application-specific intelligent sensors.”
“We are excited to add SensiML as a partner that will enable the implementation of embedded machine learning on our vast range of microcontroller and microprocessor products,” said Fanie Duvenhage, vice president of Microchip’s Human Machine Interface and Mixed-Signal and Linear business units. “The ability of the SensiML Analytics Toolkit to easily generate high-quality, power-efficient models with a small memory footprint is an excellent fit for our customers that wants to add machine learning to their existing designs.”
